A system for monitoring the state of calibration of a digital x-ray detector having a solid state sensor with a plurality of pixels, a scintillating screen and at least one embedded microprocessor, the system having means for capturing a digital image and a computer operable during normal diagnostic use of the detector, in cooperation with at least one embedded microprocessor, for performing pixelwise computations on the image and calculating a misregistration metric indicative of movement of the solid state sensor relative to the scintillating screen. A defect metric indicative of abnormal properties of pixels in the solid state sensor is calculated. It is then determined whether one or both of the misregistration metric and the defect metric exceeds a respective, preselected threshold value. The user of the system is alerted to conduct a calibration of the detector when either one or both of the respective threshold values have been exceeded.
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1. A method for monitoring the state of calibration of a digital x-ray detector, the detector comprising a solid state sensor, a scintillating screen and at least one embedded microprocessor, the solid state sensor comprising a plurality of pixels, the method comprising using a computer or the embedded microprocessor or both, during normal diagnostic use of the detector, to perform steps of: accessing a digital image including digital image data; calculating a misregistration metric from the digital image data indicative of movement of the solid state sensor relative to the scintillating screen; calculating a defect metric from the digital image data indicative of abnormal properties of pixels in the solid state sensor; determining whether one or both of the misregistration metric and the defect metric exceeds a respective, preselected threshold value; and alerting a user of the detector to conduct a calibration of the solid state sensor when either or both of the respective threshold values has been attained.
A method for monitoring the calibration of a digital X-ray detector during its normal use. The detector has a solid-state sensor with pixels, a scintillating screen, and a processor. The method involves using a computer or the detector's processor to access a digital X-ray image, calculate a "misregistration metric" showing movement between the sensor and screen, and calculate a "defect metric" indicating abnormal pixels. If either metric exceeds a set threshold, the user is alerted to calibrate the detector.
2. The method according to claim 1 , further comprising a step of correcting portions of the image for any pixel corresponding to the misregistration metric or the defect metric.
The method for monitoring X-ray detector calibration, as described previously, further includes correcting image portions affected by misregistered or defective pixels, improving image quality by compensating for sensor errors detected during the monitoring process.
3. The method according to claim 1 , wherein the detector comprises shock sensors, further comprising steps of: monitoring shock events to the detector; and correlating monitored shock events to misregistrations and defects.
The method for monitoring X-ray detector calibration, which uses misregistration and defect metrics to trigger calibration alerts, also incorporates shock sensors on the detector. It monitors for shock events and correlates these events to detected misregistrations and pixel defects, enabling identification of physical impacts causing calibration issues.
4. The method according to claim 1 , wherein the detector comprises temperature sensors, further comprising steps of: monitoring temperature events affecting the detector; and correlating temperature events to misregistrations and defects.
The method for monitoring X-ray detector calibration, which uses misregistration and defect metrics to trigger calibration alerts, also incorporates temperature sensors on the detector. It monitors temperature changes affecting the detector and correlates these changes to detected misregistrations and pixel defects, enabling identification of thermal conditions causing calibration issues.
5. The method according to claim 1 , wherein the calculating steps further comprise: correcting the image for gain, offset and defect; for each pixel in at least one region of the sensor, defining a small pixel neighborhood surrounding each pixel under analysis; deriving at least one first statistical measure from all or a subset of pixels in the small pixel neighborhood; comparing each pixel under analysis with the at least one first statistical measure; if the result of the first comparing exceeds at least one first predetermined threshold value, defining a larger pixel neighborhood surrounding the pixel under analysis; deriving at least one second statistical measure from all or a subset of pixels in the larger pixel neighborhood; comparing each pixel under analysis with the at least one second statistical measure; determining whether the at least one second statistical measure exceeds a second predetermined threshold; if the second predetermined threshold is exceeded, identifying the pixel under analysis as defective or misregistered; incrementing a misregistration counter if the difference between the pixel under analysis and the at least one first statistical measure or the at least one second statistical measure falls below a third predetermined threshold; incrementing a defective pixel counter if the difference between the pixel under analysis and the at least one first statistical measure or the at least one second statistical measure exceeds the third predetermined threshold; after all pixels of the at least one region have been analyzed, calculating current misregistration and defect metrics based on previously stored misregistration and defect metrics and the incremented misregistration and defective pixel counters; and storing the current misregistration and defect metrics on the computer or the processor or both.
The method for monitoring X-ray detector calibration, focusing on calculating misregistration and defect metrics, involves these steps: Correcting the image for gain, offset, and defects; defining a small pixel neighborhood for each pixel; deriving a first statistical measure (e.g., average) from that neighborhood; comparing the pixel to that measure; if the difference exceeds a threshold, defining a larger neighborhood; deriving a second statistical measure from the larger neighborhood; comparing the pixel to the second measure; determining if the second measure exceeds a threshold; identifying the pixel as defective or misregistered if it does; incrementing misregistration/defect counters based on exceeding or falling below another threshold; calculating current misregistration/defect metrics based on old metrics and counter increments; and storing the current metrics.
6. The method according to claim 5 , wherein each pixel or a statistical measure of the first pixel neighborhood in the at least one region is compared to a threshold code value and only pixels exceeding the code value are analyzed.
The method for monitoring X-ray detector calibration, involving statistical analysis of pixel neighborhoods, initially compares each pixel (or a statistical measure of its small neighborhood) to a code value threshold. Only pixels exceeding this code value are subjected to the more complex neighborhood analysis, optimizing the process by filtering out normal pixels and focusing on potential problem areas.
7. The method according to claim 5 , wherein deriving the at least one first statistical measure comprises sorting all or a subset of the pixel values in the small pixel neighborhood.
In the method for monitoring X-ray detector calibration, the derivation of the first statistical measure within a small pixel neighborhood involves sorting all or a subset of pixel values within that neighborhood, allowing the use of order-statistic filters (e.g., median, percentiles) to determine the central tendency or distribution of pixel values.
8. The method according to claim 5 , wherein a first statistical measure comprises one or more two-dimensional order-statistic filters.
In the method for monitoring X-ray detector calibration, a first statistical measure of a pixel's neighborhood involves using one or more two-dimensional order-statistic filters, which perform non-linear spatial filtering operations to reduce noise and highlight subtle variations, facilitating defect and misregistration detection.
9. The method according to claim 5 , wherein a second statistical measure comprises the standard deviation of a subset of sorted pixels of the larger pixel neighborhood.
In the method for monitoring X-ray detector calibration, a second statistical measure, derived from a larger pixel neighborhood, is the standard deviation of a subset of sorted pixel values. This metric represents the variability of pixel values within the larger neighborhood, providing a measure of local uniformity that can indicate misregistration or defects.
10. A method for monitoring the state of calibration of a digital x-ray detector, the detector comprising a solid state sensor, a scintillating screen and at least one embedded microprocessor, the solid state sensor comprising a plurality of pixels, the method comprising using a computer or the embedded microprocessor or both, during use of the detector, to perform: accessing a digital image including digital image data; calculating a misregistration metric from the digital image data indicative of movement of a portion of the plurality of pixels relative to the scintillating screen; calculating a defect metric from the digital image data indicative of abnormal properties of pixels in the solid state sensor; storing the misregistration and defect metrics together with ancillary system data on a processor or a computer or both; and performing an analysis of the misregistration or defect metrics, or both, as a function of at least one of the ancillary system data.
A method for monitoring the calibration of a digital X-ray detector during use, by accessing an image and calculating a "misregistration metric" showing movement of pixels relative to the screen and a "defect metric" indicating abnormal pixels. These metrics, along with "ancillary system data" (like time, operator, temperature), are stored. The misregistration and defect metrics are then analyzed in relation to this ancillary data to find correlations and patterns.
11. The method according to claim 10 , wherein the ancillary system data comprises a time, a system operator, a location, a shock or vibration value, a number of images, and a temperature.
The method for monitoring X-ray detector calibration by correlating misregistration and defect metrics with ancillary system data, where the ancillary system data includes factors like the time an image was taken, the system operator using the detector, the location of the detector, any shock or vibration experienced, the number of images taken, and the temperature, enabling analysis of environmental and usage factors impacting calibration.
12. A system for monitoring the state of calibration of a digital x-ray detector, the detector comprising a solid state sensor, a scintillating screen and at least one embedded microprocessor, the system comprising: a computer operable during normal diagnostic use of the detector to access a digital image including digital image data; processing means for performing pixelwise computations on the image and calculating a misregistration metric indicative of movement of the solid state sensor relative to the scintillating screen; processing means for calculating a defect metric indicative of abnormal properties of pixels in the solid state sensor; processing means for determining whether one or both of the misregistration metric and the defect metric exceeds a respective threshold value; and means for alerting a user of the system to conduct a calibration of the detector when either one or both of the respective threshold values have been exceeded.
A system for monitoring the calibration of a digital X-ray detector during normal use, comprising: a computer to access images; processing to calculate a "misregistration metric" showing movement between the sensor and screen; processing to calculate a "defect metric" indicating abnormal pixels; processing to determine if either metric exceeds a threshold; and an alert system to notify the user to calibrate if thresholds are exceeded.
13. The system according to claim 12 , wherein the detector is portable, comprising a battery and supporting a wireless link to the computer, where the misregistration metric operates to identify temporary changes in pixel sensitivity correctable by re-calibration.
The X-ray detector monitoring system, which calculates misregistration and defect metrics to trigger calibration alerts, is designed for a portable detector with a battery and wireless link to the computer. The misregistration metric is specifically used to identify temporary sensitivity changes that can be corrected by recalibration, maintaining image quality in mobile usage scenarios.
14. The system according to claim 12 , wherein the detector comprises at least one shock sensor for monitoring mechanical shock to the detector, and the system further comprises means for alerting a system user to conduct a calibration of the detector when a preselected shock threshold value has been exceeded.
The X-ray detector monitoring system, which calculates misregistration and defect metrics to trigger calibration alerts, includes shock sensors on the detector. If a shock event exceeds a pre-set threshold, the system alerts the user to calibrate the detector, indicating physical impact as a cause of potential miscalibration.
15. The system according to claim 12 , wherein the detector comprises at least one temperature sensor, and the system further comprises means for alerting a system user to conduct a calibration of the detector when a preselected upper or lower temperature threshold value has been exceeded.
The X-ray detector monitoring system, which calculates misregistration and defect metrics to trigger calibration alerts, includes temperature sensors on the detector. If the temperature exceeds an upper or lower pre-set threshold, the system alerts the user to calibrate the detector, indicating thermal conditions as a cause of potential miscalibration.
16. The system according to claim 12 , wherein the means for performing pixelwise computations further comprises means for correcting the identified misregistered or defective pixels, or both.
The X-ray detector monitoring system, which calculates misregistration and defect metrics to trigger calibration alerts, includes the ability to correct identified misregistered or defective pixels, improving image quality by compensating for sensor errors.
17. The system according to claim 12 , further comprising: means for conducting a calibration step; means to identify any pixels with abnormal properties that are not marked as defective in the current defect map of the detector; and means for updating the current defect map with the newly identified pixels.
The X-ray detector monitoring system, which calculates misregistration and defect metrics to trigger calibration alerts, also has: calibration functionality; identification of abnormal pixels not marked as defective; and updates its defect map with these newly identified pixels. This allows the system to continuously learn and adapt.
18. A system for monitoring the state of calibration of a digital x-ray detector, the detector comprising a solid state sensor with a plurality of pixels, a scintillating screen and at least one first computer processor, the system comprising: a first device configured to access a digital image comprising digital image data; a second computer processor operable during normal diagnostic use of the detector, in cooperation with the at least one first computer processor configured to; perform pixelwise computations on the image and calculate a misregistration metric indicative of movement of the solid state sensor relative to the scintillating screen; calculate a defect metric indicative of abnormal properties of pixels in the solid state sensor; where the misregistration and defect metrics are stored together with ancillary system data on the at least one first computer processor or the second computer processor or both; where the misregistration metric or the defect metric, or both, are displayed as a function of any ancillary system data to the system user.
A system for monitoring the calibration of a digital X-ray detector with a solid-state sensor, scintillating screen, and processor, includes a first device for accessing images and a second processor that calculates a "misregistration metric" showing movement and a "defect metric" indicating abnormal pixels. These metrics and "ancillary system data" are stored, and then the misregistration or defect metric is displayed to the user as a function of any of the ancillary data.
19. The system according to claim 18 , where the second computer processor in cooperation with the at least one first computer processor are configured to analyze the misregistration metric or defect metric, or both, as a function of at least one of the ancillary system data, where the ancillary data is any of a time, system operator, location, temperature, shock and vibration.
The X-ray detector monitoring system, which displays misregistration and defect metrics as a function of ancillary system data, analyzes these metrics using the ancillary data. The ancillary data can include time, system operator, location, temperature, shock, and vibration, providing insights into how these factors affect calibration.
20. A method for monitoring the state of calibration of a digital x-ray detector, the detector comprising a solid state sensor, a scintillating screen and at least one embedded microprocessor, the solid state sensor comprising a plurality of pixels, the method comprising using a computer or the embedded microprocessor or both, during use of the detector, the method comprising: accessing a digital image including digital image data; calculating a misregistration metric from the digital image data indicative of movement of the solid state sensor relative to the scintillating screen; storing the misregistration metric at one of the detector and the computer or displaying the misregistration metric.
A method for monitoring the calibration of a digital X-ray detector by accessing an image and calculating a "misregistration metric" indicating movement between the sensor and screen. The misregistration metric is then stored on the detector or computer, or it is displayed to the user.
21. The method of claim 20 , comprising: calculating a defect metric from the digital image data indicative of abnormal properties of pixels in the solid state sensor; determining whether one or both of the misregistration metric and the defect metric exceeds a respective, preselected threshold value, where the misregistration metric is indicative of temporary changes in pixel sensitivity correctable by re-calibration; and alerting a user of the detector to conduct a calibration of the solid state sensor when either or both of the respective threshold values has been attained.
The method for monitoring X-ray detector calibration by calculating and storing/displaying a misregistration metric also includes: calculating a defect metric indicating abnormal pixels; determining if the misregistration or defect metric exceeds a threshold. The misregistration metric indicates temporary pixel sensitivity changes that can be corrected by recalibration. If either metric exceeds its threshold, the user is alerted to calibrate.
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December 21, 2009
August 27, 2013
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